Author Affiliations: General Medicine Division, Department of Medicine, Massachusetts General Hospital and Harvard Medical School (Dr Meigs); Department of Nutrition, Harvard School of Public Health (Dr Hu); Department of Pathology, Children's Hospital Medical Center and Harvard Medical School (Dr Rifai); Division of Preventive Medicine and the Channing Laboratory, Brigham and Women's Hospital, Harvard Medical School, and the Department of Epidemiology, Harvard School of Public Health (Drs Hu and Manson), Boston, Mass.

Conclusion Endothelial dysfunction predicts type 2 diabetes in women independent
of other known risk factors, including obesity and subclinical inflammation.

Figures in this Article

Type 2 diabetes mellitus is increasingly prevalent worldwide,1 conferring major burdens on health and health care
costs. Type 2 diabetes may be largely preventable,2,3 but
a comprehensive understanding of its etiology is still needed. Development
of atherosclerotic cardiovascular disease (CVD) is the principal complication
in type 2 diabetes, but clinical CVD can also precede development of diabetes,4 lending support to the hypothesis that diabetes and
CVD share common antecedents. A syndrome of insulin resistance may constitute
this common antecedent,5 but mechanisms unifying
diverse effects of insulin resistance are not well defined. Insulin resistance
is an established factor in the pathogenesis of type 2 diabetes but has an
uncertain association with CVD.6

Subclinical inflammation could be a unifying factor because it is a
precursor of CVD, is associated with insulin resistance, and precedes development
of type 2 diabetes.7,8 Inflammatory
mediators may be pathogenic by inducing systemic endothelial dysfunction.
This hypothesis localizes insulin resistance and atherosclerosis to a unifying
tissue type: in large arteries, endothelial dysfunction leads to clinical
CVD, whereas in the capillary and arteriolar endothelium, with a vast surface
area in intimate contact with metabolically active, insulin-sensitive tissues,
endothelial dysfunction may lead to type 2 diabetes.9,10 Identification
of endothelial dysfunction as a type 2 diabetes precursor might expand options
for diabetes prevention and treatment.

Endothelial dysfunction can be detected by measurement of elevated plasma
levels of cellular adhesion molecules (CAMs), including E-selectin, intercellular
adhesion molecule 1 (ICAM-1), and vascular cell adhesion molecule 1 (VCAM-1).
Elevated levels of CAMs have been a consistent finding in cross-sectional
studies of patients with type 2 diabetes11,12 and
people at increased risk for diabetes.12- 14 Retinal
arteriolar narrowing, a marker of microvascular dysfunction, has been shown
to predict incident type 2 diabetes,15 but
prospective data directly linking endothelial dysfunction to development of
diabetes remain sparse and inconsistent.16,17 In
this study, we tested the hypothesis that elevated levels of E-selectin, ICAM-1,
and VCAM-1 predict incident type 2 diabetes in women, independent of known
diabetes risk factors, including obesity and subclinical inflammation.

METHODS

Study Participants

The Nurses' Health Study began in 1976, when 121 700 female nurses
aged 30 to 55 years and from 11 US states responded to a questionnaire of
health-related information. Questionnaires have been administered biennially
to update health information and identify new cases of disease.

During 1989-1990, 32 826 women free of diagnosed diabetes, coronary
heart disease, stroke, or cancer provided blood samples. By 2000, 737 of these
women had developed type 2 diabetes. Controls providing baseline blood samples
were matched to diabetes cases by year of birth, date of blood draw, race,
and fasting status (at least 8 hours overnight) at blood draw. In addition,
another control was matched on these characteristics and also on body mass
index (BMI) to each of the most obese cases (cases in the top 10% of the BMI
distribution). We matched the most obese cases on BMI to improve statistical
control for obesity, seeking to ensure that differences in risk of diabetes
were not a function of incomplete control of confounding by higher levels
of obesity in diabetes cases. Thus, we analyzed a sample of 785 controls.

Women who provided blood samples had a higher prevalence of obesity,
a higher prevalence of a family history of diabetes, and a lower prevalence
of current smoking but were otherwise similar to women not providing blood.
Subjects provided written informed consent, and the study was approved by
the institutional review board of Partners HealthCare System, Boston, Mass.

Ascertainment of Diabetes

Baseline and incident type 2 diabetes were identified by self-report
and confirmed by a validated supplementary questionnaire detailing symptoms,
diagnostic laboratory test results, and diabetes treatment. Women were confirmed
to have type 2 diabetes if they reported at least 1 of the following on the
supplementary questionnaire: treatment with either insulin or an oral hypoglycemic
agent, at least 1 classic symptom of diabetes (for instance, polyuria, polydipsia,
weight loss) plus an elevated plasma glucose level, or an elevated plasma
glucose level on 2 occasions. Elevated plasma glucose was defined as at least
140 mg/dL (≥7.8 mmol/L) fasting, at least 200 mg/dL (≥11.1 mmol/L) nonfasting,
or at least 200 mg/dL (≥11.1 mmol/L) 2 hours after an oral glucose tolerance
test for cases diagnosed before 1998; for cases diagnosed in 1998 and later,
the fasting plasma glucose threshold was at least 126 mg/dL (≥7.0 mmol/L).18 Women were classified with incident diabetes if they
met these criteria and were diagnosed at least 1 year after the date of blood
collection. The validity of self-reported diabetes in this cohort has been
confirmed with medical record review.19

Assessment of Diabetes Risk Factors

Every 2 years, exposure status has been updated by questionnaire, including
smoking, menopausal status and use or nonuse of postmenopausal hormone therapy,
and body weight. We calculated BMI (measured in 1988) as weight in kilograms
divided by the square of height in meters. In 1986, we assessed self-reported
waist girth. The presence or absence of a family history of diabetes in first-degree
relatives was assessed in 1982 and 1988. Information about physical activity
was obtained in 1980, 1982, 1986, 1988, and 1992. Diet and alcohol consumption
were assessed in 1980, 1984, 1986, and 1990 by using semiquantitative food
frequency questionnaires. Physical activity and diet exposures were calculated
as updated cumulative average levels. The reproducibility and validity of
the food-frequency questionnaires have been described.20 We
summarized intake of cereal fiber, glycemic load, trans-fats, and the ratio of polyunsaturated to saturated fats (scored 1-5
for each, with 5 being the most healthy intake) to create a diet score (scored
4-20), with a high diet score associated with a reduced risk of type 2 diabetes.21 Reported weights have been shown to correlate with
measured weights (r = 0.96); reported waist girth,
with measured waist circumference (r = 0.89).22,23 Physical activity assessment has
also been validated.24

Laboratory Procedures

Women providing blood samples were sent a phlebotomy kit, returning
the sample by overnight mail in a frozen water bottle. On arrival, samples
were processed and frozen in liquid nitrogen until analysis; 97% arrived within
26 hours of phlebotomy. Quality control samples were routinely frozen with
study samples; the long-term stability of plasma samples collected and stored
under this protocol has been documented.25 Study
samples were analyzed in randomly ordered case-control pairs to further reduce
systematic bias and interassay variation.

Levels of E-selectin, ICAM-1, and VCAM-1 were measured in 2002 by commercial
enzyme-linked immunosorbent assay (R & D Systems, Minneapolis, Minn).
These biomarkers are reliable markers of early atherosclerosis26 and
have modest correlations (r = 0.04-0.58) with endothelial
dysfunction assessed directly by brachial artery flow-mediated vasodilatation
or microcirculation iontophoresis methods in a variety of populations.12,27- 29 C-reactive
protein (CRP) levels were measured via a high-sensitivity latex-enhanced immunonephelometric
assay (Dade Behring, Newark, Del). Insulin levels were measured by using a
double antibody system with less than 0.2% cross-reactivity between insulin
and its precursors (Linco Research, St Louis, Mo). Hemoglobin A1c was
measured by immunoassay (Roche Diagnostics, Indianapolis, Ind). The coefficients
of variation for analytes were E-selectin, 4.50% to 6.22%; ICAM-1, 3.56%;
VCAM-1, 8.48% to 9.77%; CRP, 2.07% to 4.47%; fasting insulin, 3.52% to 11.7%;
and hemoglobin A1c, 1.9% to 3.0%.

Statistical Analysis

We conducted a prospective, nested case-control analysis of endothelial
dysfunction biomarkers as predictors of incident type 2 diabetes. We compared
baseline characteristics of study women by using t tests, χ2 tests, or Wilcoxon rank-sum tests. We used conditional logistic regression
to account for correlations introduced by matching to estimate the relative
risk and 95% confidence intervals (CIs) for levels of biomarkers predicting
type 2 diabetes. We divided the distributions of E-selectin, ICAM-1, and VCAM-1
into quintiles according to the distribution in controls and used regression
models to estimate the significance of trend in relative risk across increasing
quintiles and to estimate risk of diabetes in each quintile relative to the
lowest quintile.

Using nested regression models conditioned on matching for age, race,
and fasting status, we estimated crude relative risks of diabetes; then adjusted
for BMI, family history of diabetes, smoking, alcohol intake, diet score,
physical activity, and hormone use; further adjusted for these covariates
and levels of CRP; and finally simultaneously adjusted for all diabetes risk
factors and biomarker levels. In these analyses, we had at least 85% power
to detect a significant linear trend (2-sided P<.05)
across quintiles in which the relative risk in the top quintile relative to
the bottom was at least 1.5.30 In a subsidiary
analysis among women providing fasting blood samples, we also adjusted nested
regression models for levels of fasting insulin and hemoglobin A1c.
We used SAS (version 6.12; SAS Institute Inc, Cary, NC) for all analyses and
defined statistical significance as P<.05.

RESULTS

Women who developed type 2 diabetes during 10 years of follow-up were
more obese, had a greater prevalence of a family history of diabetes, less
alcohol use, a less favorable diet score, less physical activity, and a lower
prevalence of hormone therapy use than did controls (Table 1). Levels of fasting insulin, hemoglobin A1c,
E-selectin, ICAM-1, and VCAM-1 were all significantly higher at baseline in
women who developed diabetes compared with those who remained nondiabetic
at follow-up.

These results remained similar when waist circumference was used instead
of BMI (as in model 2, Table 2)
as an index of obesity: for E-selectin, the relative risk of diabetes in the
highest quintile was 5.08 (95% CI, 3.05-8.47); for ICAM-1, 2.46 (95% CI, 1.50-4.03);
and for VCAM-1, 1.05 (95% CI, 0.66-1.70). Inflammation may be involved in
the association between endothelial dysfunction and risk of diabetes, but
further adjustment of model 2 for levels of CRP did not eliminate associations
of E-selectin and ICAM-1 with incident diabetes (Table 2, model 3). Cellular adhesion molecules may act independently
or in a causal pathway leading to diabetes, but simultaneous adjustment for
all 3 biomarkers and other diabetes risk factors (Table 2, model 4) did not eliminate associations of E-selectin and
ICAM-1 with diabetes.

We conducted subsidiary analyses (Table 3) to ensure that the baseline sample was free of diabetes
(by excluding women with baseline hemoglobin A1c levels >6.5%);
that associations were not due to an effect of incipient diabetes on endothelial
function (by excluding cases diagnosed during the first 4 years of follow-up);
and that associations were not due to an effect of subclinical CVD at baseline
(by excluding women with incident CVD during follow-up). Although blood pressure
and plasma lipid levels have not been measured in this cohort, we attempted
to account for their possible confounding effects by adjusting models for
reported treatment for hypertension or hyperlipidemia. In all subsidiary analyses,
levels of E-selectin and ICAM-1, but not VCAM-1, remained independent predictors
of incident type 2 diabetes.

Hyperinsulinemia and hyperglycemia are potent risk factors for type
2 diabetes and may mediate effects of endothelial dysfunction on diabetes
risk. We assessed these effects in the subset of women providing fasting blood
samples in models adjusted for diabetes risk factors and levels of hemoglobin
A1c and fasting insulin (Table
4). In this analysis, elevated levels of E-selectin, but not ICAM-1
or VCAM-1, were still a significant independent predictor of incident type
2 diabetes.

Table Graphic Jump LocationTable 4. Relative Risk of Type 2 Diabetes
According to Baseline Levels of Endothelial Dysfunction Biomarkers Among the
Subset of Women With Known Hemoglobin A1c and Fasting Insulin Levels

Obesity and the mediating effects of increased adipocyte signaling could
amplify the effect of endothelial dysfunction, increasing risk for type 2
diabetes. We assessed the joint effect of BMI and levels of E-selectin, ICAM-1,
and VCAM-1 on risk of diabetes (Figure 1).
BMI and endothelial dysfunction had only additive effects on diabetes risk:
at every level of increasing BMI or E-selectin, there was a stepwise increase
in the risk of diabetes. The most obese women with the highest levels of E-selectin
had a 13.6-fold (P<.001) increased risk of diabetes
relative to the leanest women with the lowest E-selectin levels. Patterns
were similar for increasing levels of ICAM-1 and BMI (P = .02 for ICAM-1 at each level of BMI). Elevated levels of VCAM-1
did not substantially increase risk of diabetes at any level of BMI. In each
of these analyses, P values for first-order biomarker
× BMI interaction terms were not statistically significant.

BMI (calculated as weight in kilograms divided by the square of height
in meters) has been divided into 3 categories; the distribution of biomarkers,
into tertiles. The adjusted risk of diabetes among women in each category
is shown relative to women with BMI <25 and with biomarker levels in the
lowest tertile. Relative risks were conditioned on matching on age, race,
and fasting status and were adjusted for BMI, C-reactive protein, family history
of diabetes, smoking status, alcohol use, diet score, physical activity, and
postmenopausal hormone use. ICAM-1 indicates intercellular adhesion molecule
1; VCAM-1, vascular cell adhesion molecule 1. Error bars represent 95% confidence
intervals.

COMMENT

A fundamental concept underlying the insulin resistance syndrome is
that there is some shared precursor to type 2 diabetes and CVD. Insulin resistance
has been a plausible candidate for this common precursor, but specific mechanisms
whereby insulin resistance leads to both diabetes and CVD remain ill defined.
Systemic inflammation is associated with insulin resistance and incident CVD
and diabetes.7,8,31,32 A
specific mechanism whereby inflammation may contribute to these disease processes
is induction of endothelial dysfunction,33 placing
the vascular endothelium in the key unifying position in the shared pathogenesis
of CVD and diabetes. Although there is prospective evidence linking endothelial
dysfunction with incident CVD,34 previous prospective
data linking endothelial dysfunction to risk of diabetes have been indirect
and inconsistent.15- 17 In
this study, we demonstrated that elevated plasma levels of molecular biomarkers
of endothelial dysfunction were predictors of incident diabetes in a large
cohort of initially nondiabetic women. Elevated levels of E-selectin, ICAM-1,
and VCAM-1 raised the relative risk of diabetes by 1.5- to 7.5-fold. Associations
of E-selectin and ICAM-1 with diabetes were independent of the confounding
effects of usual risk factors for diabetes, and E-selectin remained a powerful
predictor even after the potentially mediating effects of obesity, inflammation,
and levels of insulin and hemoglobin A1c were accounted for.

Subclinical tissue injury and increased fat mass elevate blood levels
of inflammatory cytokines, especially tumor necrosis factor α and interleukin
6, which stimulate an acute-phase response marked by elevated levels of CRP.35 Localization of this inflammatory cascade by vascular
endothelial cells is mediated by CAMs. Their surface expression is a common
endothelial response to a variety of toxic stimuli, and their shedding into
the systemic circulation provides evidence of endothelial cell activation
and endothelial dysfunction.26 E-selectin,
expressed exclusively by endothelial cells, is absent in inactive cells but
is rapidly induced by inflammatory cytokines. ICAM-1 and VCAM-1 are expressed
by endothelial cells and leukocytes in response to inflammatory cytokines,
elevated levels of free fatty acids, oxidized low-density lipoprotein cholesterol,
and advanced glycosylation end products occurring in diabetes.36 These
CAMs facilitate leukocyte rolling, adhesion, and transmigration into the subendothelial
space, key steps in the early formation of atherosclerotic plaque. Thus, elevated
levels of CAMs represent an early marker of several pathogenic processes associated
with endothelial dysfunction and the potential development of CVD and type
2 diabetes.

Impaired endothelial function in large arterial beds is a key step in
the pathogenesis of CVD, and elevated levels of CAMs predict the incident
development of CVD events independent of standard CVD risk factors.37 Endothelial dysfunction in the capillary and arteriolar
microcirculation is a plausible key step in the evolution of tissue insulin
resistance and may act by at least 2 mechanisms. Impaired endothelium-dependent
vasodilatation and vasomotion may limit insulin-mediated capillary recruitment
and microvascular redistribution of skeletal muscle blood flow from nonnutritive
to nutritive flow routes, diminishing insulin delivery to metabolically active,
insulin-sensitive muscle tissue.10,38- 40 Also,
altered endothelial permeability impairs insulin delivery to the interstitium.
In the dynamic state, interstitial insulin levels appear to be a rate-limiting
step determining insulin effectiveness.41 In
addition to vascular insulin resistance, endothelial dysfunction is associated
with impaired fibrinolysis, microalbuminuria, impaired function of insulin-sensitive
lipoprotein lipase (contributing to a dyslipidemia with high triglyceride
and low high-density cholesterol levels), impaired fibrinolysis, and impaired
endothelium-dependent nitric-oxide–mediated vasodilatation (contributing
to hypertension), all features of the insulin resistance syndrome.9,10 Recent experimental evidence in humans
has placed endothelial dysfunction in a direct link between blood pressure
and insulin sensitivity.42 The results of our
analysis extend observations linking endothelial dysfunction to CVD and its
risk factors, strengthening support for the hypothesis that endothelial dysfunction
is also an important precursor of type 2 diabetes.

Results of our study extend other evidence linking endothelial dysfunction
to insulin resistance and risk of diabetes. Mice with endothelial dysfunction
by virtue of targeted knockout mutations in the endothelium-dependent nitric
oxide synthase gene are insulin resistant and display features of the insulin
resistance syndrome.43 Endothelial dysfunction
is a consistent finding in cross-sectional studies of established diabetes.11,12,44,45 Endothelial
dysfunction and elevated levels of E-selectin, ICAM-1, and VCAM-1 have also
been described in cross-sectional studies of nondiabetic subjects at increased
risk of diabetes, including subjects with impaired glucose tolerance, and
in nondiabetic first-degree relatives of patients with type 2 diabetes.12- 14,46 Three
previous epidemiologic studies have examined risk of incident diabetes. In
the Atherosclerosis Risk in Communities (ARIC) Study, microcirculatory dysfunction,
represented by retinal arteriolar narrowing, increased risk for diabetes by
71%, comparing subjects in the highest quartile of narrowing with those in
the lowest quartile.16 Also in ARIC, levels
of von Willebrand factor, another endothelial biomarker, was not an independent
predictor of incident diabetes after BMI was accounted for, although coagulation
factor VIII was an obesity-independent predictor of diabetes in women.16 In a study of 71 Pima Indians, elevated levels of
several biomarkers, including E-selectin and ICAM-1, were not independently
associated with incident diabetes.17 Treatment
with drugs having beneficial effects on endothelial function also supports
an association with insulin resistance and risk of diabetes. Insulin sensitization
with troglitazone or metformin in type 2 diabetes lowers E-selectin levels,
improves endothelium-dependent vasodilatation, and, when used in patients
without diabetes, reduces risk of developing diabetes.3,47- 50 Therapy
with statins51 or angiotensin-converting enzyme
(ACE) inhibitors52 improves insulin sensitivity
and endothelial dysfunction and, in secondary analyses of CVD prevention studies,
has been associated with an approximately 30% reduced risk of incident diabetes.53,54 However, whether amelioration of
endothelial dysfunction by using statins or ACE-based therapies will actually
prevent type 2 diabetes remains to be confirmed in clinical trials.

Our study has several limitations. We assessed endothelial dysfunction
solely by means of plasma biomarkers and do not have other measures of vascular
physiology. However, although expression of CAMs represents a specific, early
stage in the evolution of endothelial dysfunction, plasma levels have modest
correlations with directly assessed endothelial function.12,27- 29 Our
comprehensive assessment of diabetes risk factors allowed statistical control
for important confounding factors in the pathogenesis of diabetes, but residual
confounding could remain in the analysis. In particular, we did not measure
levels of free fatty acids, atherogenic lipoproteins, or adipokines (for instance,
adiponectin), known mediators of endothelial dysfunction and insulin resistance.
Also, we measured only plasma insulin levels and did not have direct measurements
of insulin resistance. Although plasma insulin levels in the physiologic range
can induce insulin resistance in humans,55 statistical
control for insulin levels attenuated but did not eliminate associations of
E-selectin with incident diabetes. In addition, we were able to control for
obesity only by using BMI or waist circumference because we did not have more
precise measures of body fat percentage or fat distribution. However, for
levels of E-selectin at least, the association with diabetes remained strong
even after extensive covariate adjustment. Although residual confounding by
incompletely measured or unmeasured physiologic covariates may exist in our
models, it seems unlikely that more complete statistical adjustment would
completely eliminate the observed associations.

In addition, although hyperglycemia may lead to endothelial dysfunction,56 our prospective study design and similar effects
after subsidiary analyses excluding cases diagnosed during the first 4 years
of follow-up or excluding women with hemoglobin A1c levels higher
than 6.5% support the conclusion that endothelial dysfunction preceded development
of diabetic hyperglycemia. Further, although undetected subclinical atherosclerosis
(which occurs in prediabetes and is associated with elevated levels of CAMs)
might explain the observed associations, removal of data for women with incident
CVD during follow-up did not alter the results. These findings indicate that
baseline endothelial dysfunction was not a consequence of undetected, coincident
diabetes or atherosclerosis but was an early abnormality clearly preceding
the subsequent development of type 2 diabetes. Finally, the analysis was conducted
in relatively healthy white women aged 30 to 55 years (range, 41-67 years
at baseline). Results may not be generalizable to women of other ages or ethnic
backgrounds or to men.

In conclusion, we found that elevated plasma levels of biomarkers reflecting
endothelial dysfunction were powerful independent predictors of type 2 diabetes
in initially healthy women. Our findings support the hypothesis that endothelial
dysfunction may be a common pathogenic precursor to CVD and type 2 diabetes,
placing endothelial dysfunction as a fundamental abnormality in the insulin
resistance syndrome. These findings may have important implications for the
prevention and treatment of type 2 diabetes. Therapies that improve endothelial
dysfunction may prove important in the treatment of insulin resistance and
in strategies to slow the accelerating worldwide epidemic of type 2 diabetes
and its costly, morbid complications.

Freeman DJ, Norrie J, Sattar N.
et al. Pravastatin and the development of diabetes mellitus: evidence for
a protective treatment effect in the West of Scotland Coronary Prevention
Study. Circulation.2001;103:357-362.PubMed

BMI (calculated as weight in kilograms divided by the square of height
in meters) has been divided into 3 categories; the distribution of biomarkers,
into tertiles. The adjusted risk of diabetes among women in each category
is shown relative to women with BMI <25 and with biomarker levels in the
lowest tertile. Relative risks were conditioned on matching on age, race,
and fasting status and were adjusted for BMI, C-reactive protein, family history
of diabetes, smoking status, alcohol use, diet score, physical activity, and
postmenopausal hormone use. ICAM-1 indicates intercellular adhesion molecule
1; VCAM-1, vascular cell adhesion molecule 1. Error bars represent 95% confidence
intervals.

Freeman DJ, Norrie J, Sattar N.
et al. Pravastatin and the development of diabetes mellitus: evidence for
a protective treatment effect in the West of Scotland Coronary Prevention
Study. Circulation.2001;103:357-362.PubMed

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